Kimco acquired RPT Realty. I provided ongoing support for all data questions related to the RPT portfolio.

Led a $1M Salesforce implementation project where I set the requirements with business partners and drove the end results. I was the primary tech support for all things data integration - which continued into the merger due diligence.Plus I ran all the daily data responsibilities including managing dashboards, reports, documentation and all end user training.

Here's some things I do at RPT:-Automate manual processes (saved at least 35 hours of manual data loading processes every month)-Replace manually generated reports with automated dashboards - saving hours of time generating reports-Document key data metrics and own data governance process-Create data driven models to support RPT's strategic investments-Reduce the spend on outside consultants and vendors and keep the complexity of RPT's IT environment low

Petram Data is an Artificial Intelligence startup working to automate marketing campaigns for small to medium businesses who sell high ticket low frequency items.I was the second Detroit-based data scientist brought on to lead initiatives with key 3rd party data partners like Quicken Loans (home mortgages) and a major credit card processor. In this role, I play an essential part in project planning, hiring, creating ideas and business use cases, developing data models, and educating my peers on what's possible to achieve in the world of data.Being part of a startup, I have had the opportunity to wear many hats and find what roles suited me. I serve a key contributor and -Primary subject matter expert on ML and AI responsible for creating the proprietary model offerings based on 1st party retail and marketing campaign data-Interfaced with clients and managed the product planning with an off-shore development team to integrate data solutions with actionable insights-Work with pre-sales team and project managers to develop compelling material (decks and SOWs) to highlight the value-add of consulting engagements for marketing firms-Performed code reviews and developed a code architecture for ML solutions while mentoring junior developers.

In 2015, Wired published an article that changed how the automotive industry valued cybersecurity. Imagine this: anyone anywhere can break into your car's computer systems and turn on the radio at full volume....while you're driving 70mph on a highway. Scared? That's exactly what researchers did to a Wired journalist (https://www.youtube.com/watch?v=MK0SrxBC1xs).I was the first data science hire in Product Cybersecurity brought on to handle all things data related to long-term cybersecurity risk strategy. I have first hand experience working with petabytes of telemetry data coming from vehicles. During my three years at GM, I spearheaded many initiatives including-Interfacing between security engineers, architects and software developers to create a custom SIEM for vehicle related data.-Evaluating all data strategies that affected vehicle cybersecurity - including working internally with traditional IT cybersecurity for telematics logs and externally with vehicle cybersecurity vendors.-Earning a patent for developing a Command and Control system for on-vehicle intrusion detection.-Interfacing with other internal business groups to further the adoption of best practices in monitoring and responding to cybersecurity events.-Creating a cross-functional group of vehicle engineers to develop a solution for a more complete software Asset Inventory which was a major issue for all cybersecurity groups at GM.Outside my roles and responsibilities, I was also an active member of GM's global analytics network. I was recognized several times for proactively contributing and helping other people solve problems. During larger group activities like hackathons, I helped mentor other groups on what data GM had available and how to best use it to solve critical business problems.

I was the second data scientist, hired as an apprentice (contract), to kickstart machine learning intiatives at CoverMyMeds. During my time there, I:-Created a machine learning product from design to production with XGboost that was a 70% improvement over the prior statistical solution.-Worked cross-functionally building relationships with software developers, system administrators, and field sales team to successfully build and sell ML products to 3 customers.-Using Agile development, established a code base for data science applications at CMM using github repos with regular code reviews.

I was in charge of managing a team of 6 people for several months out of the year. I scheduled their working time and outlined the tasks that needed to be completed by each team member. I was responsible for reviewing their work and making sure everyone stayed on target.Labs usually have high turnover rates because of the nature of grad school. I was in charge of documenting the problem solving steps I took in each of my projects and the solutions that worked best. This documentation needed to be easy to follow for future lab members (or other interested parties) that I might not interact with face-to-face.The lab generated a large amount of data. I had to work with a team of other graduate students to figure out the best way to store this information so it was useful to the lab as a whole. The type of physics I was working on relied heavily on statistics and network theory.